In 2022 we have seen a great increase in the world of web technologies and web development, in this article we will look at one of the fastest growing careers which is becoming a React JS front-end developer in 2022, we will look at a detailed road-map on how you can excel at today’s leading tech careers. Here is The ultimate road-map to becoming a React JS software developer:
In this article we will be taking a deeper dive how React JS and Django and be used in an application:
A notable benefit of employing Django for back-end web development is the fact that it’s a Representational State Transfer (REST) framework, which makes it a popular toolkit for building APIs. One of the main benefits of REST APIs is that they offer a great deal of flexibility. Hence, Django REST framework is essentially a highly powerful, scalable, and versatile toolkit for constructing web APIs.
With regards to merging Django and React technologies, it’s essentially a canonical combination for building web software. In practice, an application that combines both technologies will have Django as back-end and ReactJS as front-end. Simply put, this means that the REST API calls the back-end, if any data is needed in the front-end. Since front-end frameworks require a RESTful API to interact with, developers can choose to create a RESTful back-end API with Django.
Django (back-end Python technology)
-Django components: View, Model, Template, URLs, Admin
-Django will run on a different server but in the same environment
-React components: State, Props, Forms, Hooks
-React will run on a different client but in the same environment
-Together they will communicate through HTTPS requests or AJAX
-Powerful Front-end and powerful back-end
Businesses and organizations have long used business reporting and data analytics on a tactical basis, answering such questions as “just what were sales in Wisconsin in 2021?” But in recent years big
data management and analytics has become more strategic, spurred by digital transformation initiatives, efforts to leverage data for competitive advantage
and even moves to monetize data assets.
More immediately, with the COVID-19 pandemic and its economic disruptions, businesses now realize the need to better utilize data for such tasks as managing supply chains and retaining employees. And the wave of cybersecurity incidents making headlines has brought home the importance of stepping up their data governance operations. All this is changing how businesses collect, manage, utilize and analyses their growing volumes of data.
2) What is a Data Engineer:
Data engineers work in a variety of settings to build systems that collect, manage, and convert raw data into usable information for data scientists and business analysts to interpret.
Their ultimate goal is to make data accessible so that organizations can use it to evaluate and optimize their performance.
-What tools and techniques do a Data Engineer need and use:
1) Coding skills in Python, R, Java
2) Data Lakes and Data Warehousing
3) ETL (Extraction, Transformation and Load) with data
4) Database Systems
5) Good soft skills
6) Basic understanding of Machine and Deep learning
-What is the earning potential for a Data Engineer?:
£85K. Average: £6,517Range: £1,234 - £34,431. The average salary for Data Engineer is £52,281 per year in the London Area. The average additional cash compensation for a Data Engineer in the London Area is £6,517, with a range from £1,234 - £34,431.
3) What is a Data Analyst?:
Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. A data analyst collects, processes and performs statistical analyses on large dataset. They discover how data can be used to answer questions and solve problems. With the development of computers and an ever increasing move toward technological intertwinement, data analysis has evolved. The development of the relational database gave a new breath to data analysts, which allowed analysts to use SQL (pronounced “sequel” or “s-q-l”) to retrieve data from databases.
-What does it take to become a Data Analyst?:
1) Creative and Critical Thinking
2) Data Visualization
3) Data Manipulation, Mining and Extraction
4) Great communication skills
5) SQL and Databases